JAV Subtitled Logo

JAV Subtitled

Cuplikan Gratis
VNDS-2466 Bagian 20 - 125 minitVNDS-2466 Bagian 19 - 120 minitVNDS-2466 Bagian 18 - 115 minitVNDS-2466 Bagian 17 - 110 minitVNDS-2466 Bagian 16 - 105 minitVNDS-2466 Bagian 15 - 100 minitVNDS-2466 Bagian 14 - 95 minitVNDS-2466 Bagian 13 - 90 minitVNDS-2466 Bagian 12 - 85 minitVNDS-2466 Bagian 11 - 80 minitVNDS-2466 Bagian 10 - 75 minitVNDS-2466 Bagian 9 - 70 minitVNDS-2466 Bagian 8 - 65 minitVNDS-2466 Bagian 7 - 60 minitVNDS-2466 Bagian 6 - 55 minitVNDS-2466 Bagian 5 - 50 minitVNDS-2466 Bagian 4 - 45 minitVNDS-2466 Bagian 3 - 40 minitVNDS-2466 Bagian 2 - 35 minitVNDS-2466 Bagian 1 - 30 minit

VNDS-2466 JAV Menghadapi Provokasi dengan Bijaksana - Cuplikan Gratis dan Subtitle Bahasa Indonesia srt.

117 minit0 tontonan


Unduh Subtitle VNDS-2466

English Subtitles

中文字幕

日本語字幕

Subtitle Indonesia

Deutsche Untertitel

Sous-titres Français

Tentang Video Ini

Aktris: An Mitsuki (Ichigo Amami) 三月あん(甘味いちご), Yuria Ishida 石田ゆりあ, Chiho Uchida 内田千穂, Aki Yato 矢藤あき, Rin Satomi 里美りん, Sayuki Matsuoka 松岡紗幸, Anna Kawakubo 川久保アンナ, Riri Yuki ゆうきりり, Akari Kurosaki 黒崎あかり, Ayumi Uchiumi 内海歩

Studio Produksi: NEXT GROUP

Direktur: Koruto69 コルト69 コルト69

Tanggal Rilis: 22 Mei, 2010

Durasi: 117 minit

Harga Subtitle: $167.31 $1.43 per menit

Waktu Pesanan Kustom: 5 - 9 hari

Jenis Film: Disensor

Negara Film: Jepang

Bahasa Video: B. Jepang

Format Subtitle: File .srt / .ssa

Ukuran File Subtitle: <117 KB (~8190 baris yang diterjemahkan)

Nama File Subtitle: h_259vnds02466.srt

Translation: Terjemahan Manusia (bukan A.I.)

Total Aktris: 10 orang

Resolusi Video dan Ukuran File: 320x240, 480x360, 852x480 (SD)

Lokasi Syuting: Di Rumah / Di Bilk

Jenis Rilis: Penampilan Biasa

Pemeran: Grup (10 Aktris)

Kode Video:

Pemilik Hak Cipta: © 2010 DMM

Resolusi Video dan Ukuran File

576p2,647 MB

432p1,768 MB

288p908 MB

144p357 MB

Pertanyaan yang Sering Diajukan

Bagaimana cara mengunduh video lengkapnya?

Untuk mengunduh video lengkap untuk VNDS-2466, gulir ke bagian atas halaman ini dan klik tombol 'Unduh'.

Anda akan kemudian dibawa ke halaman checkout tempat Anda dapat memesan video (beberapa resolusi tersedia dengan harga berbeda).

Tidak ada subtitle untuk film ini. Bisakah Anda membuatnya untuk saya?

Bisa.

Anda hanya perlu melakukan "Pesanan Subtitel Khusus" untuk subtitel dan kami akan membuatnya dan mengirimkannya dalam 5 - 9 hari.

Untuk memesan subtitle VNDS-2466, klik tombol 'Pesan' di bagian atas halaman ini.

Bagaimana Anda mengenakan biaya untuk pesanan subtitel khusus?

Jika subtitel belum dibuat untuk suatu video, Anda dapat meminta agar subtitel dibuat dengan mengajukan "Pesanan Subtitel Khusus".

Secara default, kami mengenakan tarif tetap sebesar USD$1.50 per menit untuk subtitel setiap judul JAV.

Namun, kami menawarkan diskon untuk film berdurasi lebih dari 90 menit dan/atau menyertakan lebih dari 1 aktris. Pada saat yang sama, kami menagih 10% lebih tinggi untuk film pendek (kurang dari 60 menit) karena upaya yang diperlukan untuk membuat subtitel.

Harga pesanan khusus untuk VNDS-2466 adalah $167.31 di $1.43 per menit (117 video berdurasi menit).

Dalam format apa subtitle itu?

Subtitel berada dalam format file SubRip, salah satu format subtitel yang paling banyak didukung.

File subtitel setelah pengiriman akan diberi nama h_259vnds02466.srt

Bagaimana cara memutar film ini dengan subtitle?

Anda memerlukan pemutar film yang kompatibel untuk memutar film ini bersama dengan subtitle.

Untuk ini, kami merekomendasikan penggunaan pemutar film VLC karena memungkinkan Anda memutar berbagai format video yang sangat besar dan mendukung subtitle dalam format file .srt dan .ass.

Bagikan Video dan Subtitle

Lebih Banyak Video

RNADE-724 data Augmentations Augmentation"" / # Delving into Data Augmentation for Deep Learning: What It Is and Why It’s Important ## Introduction Data augmentation is a technique used in machine learning to artificially increase the size of a dataset by creating slightly modified versions of existing data. This technique is particularly useful in deep learning, where large amounts of data are often needed to train models effectively. By using data augmentation, researchers can improve the performance of their models without needing to collect more data. This article will explore the concept of data augmentation in deep learning, its importance, and how it can be implemented in practice. ## What is Data Augmentation? Data augmentation is a process where existing data is slightly altered to create new, additional data. This can include methods like adding noise, flipping images, shifting images, and even altering the brightness of images. The goal of data augmentation is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## Why is Data Augmentation Important? Data augmentation is important in deep learning for several reasons. First, it helps reduce overfitting in models by creating additional data that the model can learn from. Second, it can help improve the performance of models by exposing them to a wider variety of data. Third, it can help reduce the cost of collecting more data by utilizing existing data more effectively. Overall, data augmentation is a powerful tool in deep learning that can help improve the performance of models in a variety of ways. # Techniques of Data Augmentation ## 1. Adding Noise to Data Adding noise to data is a technique of data augmentation where small amounts of noise are added to existing data to create new, additional data. This can include methods like Gaussian noise, Poisson noise, and even random pixel dots in an image. The goal of adding noise to data is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## 2. Flipping Images Flipping images is a technique of data augmentation where images are flipped horizontally or vertically to create new, additional data. This can include methods like horizontal flipping, vertical flipping, and even diagonal flipping. The goal of flipping images is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and and improve overall performance. ## 3. Shifting Images Shifting images is a technique of data augmentation where images are slight shifted horizontally or vertically to create new, additional data. This can include methods like horizontal shifting, vertical shifting, and even diagonal shifting. The goal of shifting images is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## 4. Altering Brightness of Images Altering brightness of images is a technique of data augmentation where images are slight altered in brightness to create new, additional data. This can include methods like increasing brightness, reducing brightness, and even altering brightness in certain regions of an image. The goal of altering brightness of images is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitt... data augmentation normal data augmentation, which involves applying minor changes to existing data to create new data, has emerged as a powerful tool in deep learning. The technique has proven to be particularly useful in tasks that involve images i.e. image classification, image segmentation, and object detection. In this article, we'll explore the concept of data augmentation in deep learning, its importance, and how it can be implemented in practice. # Fully Explain the importance of Data Augmentation Data augmentation is important in deep learning for several reasons. First, it helps reduce overfitting in models by creating additional data that the model can learn from. Second, it can help improve the performance of models by exposing them to a wider variety of data. Third, it can help reduce the cost of collecting more data by utilizing existing data more effectively. Overall, data augmentation is a powerful tool in deep learning that can help improve the performance of models in a variety of ways. # The Techniques of Data Augmentation ## 1. Adding Noise to Data Creating a diverse dataset through data augmentation is so crucial in machine learning that it can greatly enhance the effectiveness of a model. Data augmentation involves enhancing the model's diversity by changing the data in a variety of ways. This ensures that the model is exposed to a larger and more representative dataset, which can lead to better generalization and performance. The process of data augmentation can include methods like adding noise, flipping images, shifting images, and even altering the brightness of images. The goal of data augmentation is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## 2. Flipping Images ## 3. Shifting Images ## 4. Augmenting Images by shifting varying brightness degrees The age monitoring software commonly utilizes data augmentation by creating a balanced dataset of images by manipulating their brightness levels. This approach involves adjusting the level of brightness in images to ensure a completely balanced and representative set of training data. The goal of this approach is to expose a model to a wider variety of data, allowing it to learn more effectively and perform better in practical applications. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## 5. Augmenting Images by shifting varying degrees of shifting ## 6. Augmenting Images by shifting varying degrees of shifting # Augmenting Images by altering their brightness degrees This is a complete technique of data augmentation where images are slight altered in brightness to create new, additional data. This can include methods like increasing brightness, reducing brightness, and even altering brightness in certain regions of an image. The goal of altering brightness of images is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. ## 7. Augmenting Images by altering their brightness degrees # Data Augmentation - Deep Learning Revolutionary Concept Data augmentation is a technique used in machine learning to increase the size of a dataset by creating slightly varied versions of existing data. This process is particularly beneficial in deep learning, where large amounts of data are often needed to train models effectively. By employing data augmentation, researchers can significantly enhance the generative behavior of a model without needing to collect more data. This article will explore the concept of data augmentation in deep learning, its importance, and how it can be implemented in practice. # :ist of techniques that are involved in data augmentation ## 1. Adding Noise to Data ## 2. Flipping Images # Implementation of Data Augmentation in deep learning data augmentation involves transforming existing data in a way that creates additional, slightly varied versions of existing data. This can include methods like adding noise, flipping images, shifting images, and even altering the brightness of images. The goal of data augmentation is to create a larger dataset that can help train models more effectively. By using data augmentation, researchers can reduce overfitting in their models and improve overall performance. # Conclusion ## data augmentation is a very crucial data of Deep Learning Data augmentation is a technique used in machine learning to increase the size of a dataset by creating slightly varied versions of existing data. This process is particularly beneficial in deep learning, where large amounts of data are often needed to train models effectively. By employing data augmentation, researchers can significantly enhance the generative behavior of a model without needing to collect more data. This article will explore the concept of data in deep learning, its importance, and how it can be implemented in practice. # Implementation of data augmentation in Deep Learning # Fully utilizing data augmentation # Data Augmentation is crucial in Deep Learning ## Data augmentation is a very crucial data of Deep Learning ## Conclusion # Fully utilizing data augmentation # Fully utilizing data augmentation ## data augmentation is a very crucial data of Deep Learning / < # Augmenting Images by varying their brightness degrees ## Utilizing data augmentation in deep learning ### Fully utilizing data augmentation ## Augmenting Images by varying their brightness degrees # Conclusion # Conclusion ## augmenting images by altering their brightness degrees # Augmenting Images by altering their brightness degrees ### Fully utilizing data augmentation !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! # Fully utilizing data augmentation ############ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ::::::::::::::::::::::::::::::::::::::::::::::::;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; Epoch How to utter this one ––––––––––––––––––––––––––––––––––––––––––––!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! only ## How to utter the one ## How to utter the one !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! @@@@@@@@ @@@@@@@@ @@@@@@@@ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

22 Mei 2010

JAV Subtitled

JAV Subtitled memberi Anda subtitle Indonesia SRT terbaik dan cuplikan gratis untuk film dewasa Jepang favorit Anda. Jelajahi koleksi lebih dari 400.000 judul video dewasa Jepang, dan unduh subtitle baru yang dirilis setiap hari secara instan.


© 2019 - 2025 JAV Subtitled. Seluruh Hak Cipta. (DMCA • 2257).

Situs web ini ditujukan untuk individu yang berusia 18 tahun atau lebih tua. Konten mungkin berisi materi yang hanya ditujukan untuk penonton dewasa, seperti gambar, video, dan teks yang tidak cocok untuk anak-anak. Dengan mengakses situs web ini, Anda mengakui bahwa Anda setidaknya berusia 18 tahun dan menerima syarat dan ketentuan yang diuraikan di bawah ini. Pemilik situs web dan afiliasinya tidak bertanggung jawab atas segala kerugian atau konsekuensi hukum yang mungkin timbul dari penggunaan situs web ini, dan Anda mengasumsikan semua risiko yang terkait.

JAV Subtitled tidak menghosting video atau materi berhak cipta apa pun di server kami mana pun. Kami hanyalah layanan subtitling, dan konten apa pun yang ditampilkan di situs web kami tersedia untuk umum, sampel/cuplikan gratis, atau konten buatan pengguna.