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Data (image) augmentation is a popular technique used in Deep Learning in order to increase the training performance of a model by enlarging the given dataset. Here I presented simple Matlab code f…
Implement Data Augmentation In MATLAB
ImageNet Classification with Deep Convolutional Neural Networks
👁 Vision : Model 1: AlexNet : Image Classification
Some tools and examples for pyCaffe including LMDB I/O, custom Python layers and monitoring training error and loss.
⚡ Caffe real-time data augmentation on-the-fly!!
a branc caffe with feature of Data Augmentation using a configurable stochastic combination of 7 data augmentation techniques.
Optimus: the first large-scale pre-trained VAE language model
Optimization Modeling Using mip Solvers and large language models
GenWorld: Towards Detecting AI-generated Real-world Simulation Videos
SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis
Official code for paper: Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs.
Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection
MARS: Mask Attention Refinement with Sequential Quadtree Nodes for Car Damage Instance Segmentation
[ACL 2025] VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward Mechanism
StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams
Landsat-Bench: Datasets and Benchmarks for Landsat Foundation Models
[CVPR 2025 🔥] DiscoVLA: Discrepancy Reduction in Vision, Language, and Alignment for Parameter-Efficient Video-Text Retrieval
Implementation of paper "Inherently Faithful Attention Maps for Vision Transformers"