Navigation Menu
Search code, repositories, users, issues, pull requests..., provide feedback.
We read every piece of feedback, and take your input very seriously.
Saved searches
Use saved searches to filter your results more quickly.
To see all available qualifiers, see our documentation .
- Notifications You must be signed in to change notification settings
Official Repo for Deep Learning for Compyter Vision Course offered by NPTEL
DL4CV-NPTEL/Deep-Learning-For-Computer-Vision
Folders and files, repository files navigation, deep-learning-for-computer-vision, fall 2022 link : https://onlinecourses.nptel.ac.in/noc22_cs76/preview, lectures: https://www.youtube.com/watchv=rfavjcf1_zi&list=plyqspqzte6m_pi-riz4o1jegffhju9ggg, course cirriculum, week 1:introduction and overview:.
Course Overview and Motivation; Introduction to Image Formation, Capture and Representation; Linear Filtering, Correlation, Convolution
Week 2:Visual Features and Representations:
Edge, Blobs, Corner Detection; Scale Space and Scale Selection; SIFT, SURF; HoG, LBP, etc.
Week 3:Visual Matching:
Bag-of-words, VLAD; RANSAC, Hough transform; Pyramid Matching; Optical Flow
Week 4:Deep Learning Review:
Review of Deep Learning, Multi-layer Perceptrons, Backpropagation
Week 5:Convolutional Neural Networks (CNNs):
Introduction to CNNs; Evolution of CNN Architectures: AlexNet, ZFNet, VGG, InceptionNets, ResNets, DenseNets
Week 6:Visualization and Understanding CNNs:
Visualization of Kernels; Backprop-to-image/Deconvolution Methods; Deep Dream, Hallucination, Neural Style Transfer; CAM,Grad-CAM, Grad-CAM++; Recent Methods (IG, Segment-IG, SmoothGrad)
Week 7:CNNs for Recognition, Verification, Detection, Segmentation:
CNNs for Recognition and Verification (Siamese Networks, Triplet Loss, Contrastive Loss, Ranking Loss); CNNs for Detection: Background of Object Detection, R-CNN, Fast R-CNN, Faster R-CNN, YOLO, SSD, RetinaNet; CNNs for Segmentation: FCN, SegNet, U-Net, Mask-RCNN
Week 8:Recurrent Neural Networks (RNNs):
Review of RNNs; CNN + RNN Models for Video Understanding: Spatio-temporal Models, Action/Activity Recognition
Week 9:Attention Models:
Introduction to Attention Models in Vision; Vision and Language: Image Captioning, Visual QA, Visual Dialog; Spatial Transformers; Transformer Networks
Week 10:Deep Generative Models:
Review of (Popular) Deep Generative Models: GANs, VAEs; Other Generative Models: PixelRNNs, NADE, Normalizing Flows, etc
Week 11:Variants and Applications of Generative Models in Vision:
Applications: Image Editing, Inpainting, Superresolution, 3D Object Generation, Security; Variants: CycleGANs, Progressive GANs, StackGANs, Pix2Pix, etc
Week 12:Recent Trends:
Zero-shot, One-shot, Few-shot Learning; Self-supervised Learning; Reinforcement Learning in Vision; Other Recent Topics and Applications
Contributors 3
- Jupyter Notebook 100.0%
Category: Nptel Assignment Answers 2024
Nptel introduction to industry 4 and industrial iot week 9 assignment answers, ethical hacking nptel week 9 assignment answers, digital circuits week 9 nptel assignment answers, cloud computing nptel week 9 assignment answers, computer architecture nptel week 9 assignment answers 2024, cyber security and privacy week 9 nptel answers 2024, deep learning iit ropar week 9 nptel assignment answers, deep learning for computer vision week 9 nptel answers 2024, programming in java nptel week 9 assignment answers, soft skills nptel week 9 assignment answers.
Deep Learning
Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.
Page Visits
Course layout, books and references, instructor bio.
Prof. Prabir Kumar Biswas
Course certificate.
DOWNLOAD APP
SWAYAM SUPPORT
Please choose the SWAYAM National Coordinator for support. * :
IMAGES
VIDEO
COMMENTS
Welcome to our detailed walkthrough of the "NPTEL Deep Learning Week 8 Assignment Solution for August 2024," presented by IIT Ropar.
NPTEL-Deep Learning (IIT Ropar)- Assignment 8 Solution (2024)Assignment-8 for Week-8 can be accessed from the following linkink: https://onlinecourses.nptel....
#deeplearning #nptel #ateeq10Deep Learning In this video, we're going to unlock the answers to the Deep Learning questions from the NPTEL 2023 Jul-Dec assign...
Are you looking for the Deep Learning IIT Ropar Week 8 NPTEL Assignment Answers 2024 (July-Dec)? You’ve come to the right place! Access the most accurate and up-to-date solutions for your Week 8 assignment in the Deep Learning course offered by IIT Ropar.
Each week-XX.md file provides detailed solutions and explanations for that week’s assignments. Review these files to find the information you need. By following these steps, you can easily locate and use the assignment answers and solutions for the NPTEL courses provided in this repository.
Week 8:Recurrent Neural Networks (RNNs): Review of RNNs; CNN + RNN Models for Video Understanding: Spatio-temporal Models, Action/Activity Recognition. Week 9:Attention Models: Introduction to Attention Models in Vision; Vision and Language: Image Captioning, Visual QA, Visual Dialog; Spatial Transformers; Transformer Networks.
Deep Learning - IIT Ropar : Assignment 8 Reevaluations!! Dear Learners, Assignment 8 submission of all students has been reevaluated by updating the answer for Question 4. Students are requested to find their revised scores of Assignment 8 on the Progress page.
In this course we will learn about the building blocks used in these Deep Learning based solutions. Specifically, we will learn about feedforward neural networks, convolutional neural networks, recurrent neural networks and attention mechanisms.
We provide you NPTEL Assignment Answers 2024 and solutions of all courses. Week 1,2,3, 4, 5, 6, 7 , 8, 9, 10 ,11, 1. By Swayam platform.
Week 8: Effective training in Deep Net- early stopping, Dropout, Batch Normalization, Instance Normalization, Group Normalization