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07/10/2023
SPLAL: Similarity-based pseudo-labeling with alignment loss for semi-supervised medical image classification
Medical image classification is a challenging task due to the scarcity o...
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07/10/2023
Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey
End-to-End driving is a promising paradigm as it circumvents the drawbac...
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10/19/2022
Attaining Class-level Forgetting in Pretrained Model using Few Samples
In order to address real-world problems, deep learning models are jointl...
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12/23/2021
DILF-EN framework for Class-Incremental Learning
Deep learning models suffer from catastrophic forgetting of the classes ...
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06/30/2021
Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation
Deep learning models generally learn the biases present in the training ...
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06/12/2021
Knowledge Consolidation based Class Incremental Online Learning with Limited Data
We propose a novel approach for class incremental online learning in a l...
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03/30/2021
Rectification-based Knowledge Retention for Continual Learning
Deep learning models suffer from catastrophic forgetting when trained in...
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03/01/2021
Few-Shot Lifelong Learning
Many real-world classification problems often have classes with very few...
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11/22/2020
RNNP: A Robust Few-Shot Learning Approach
Learning from a few examples is an important practical aspect of trainin...
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06/29/2020
Improving Few-Shot Learning using Composite Rotation based Auxiliary Task
In this paper, we propose an approach to improve few-shot classification...
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06/08/2020
Passive Batch Injection Training Technique: Boosting Network Performance by Injecting Mini-Batches from a different Data Distribution
This work presents a novel training technique for deep neural networks t...
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05/27/2020
AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings
In this paper, we solve for the problem of generalized zero-shot learnin...
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05/26/2020
Minimizing Supervision in Multi-label Categorization
Multiple categories of objects are present in most images. Treating this...
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01/15/2020
A "Network Pruning Network" Approach to Deep Model Compression
We present a filter pruning approach for deep model compression, using a...
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01/05/2020
Cooperative Initialization based Deep Neural Network Training
Researchers have proposed various activation functions. These activation...
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10/21/2019
CPWC: Contextual Point Wise Convolution for Object Recognition
Convolutional layers are a major driving force behind the successes of d...
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05/11/2019
Play and Prune: Adaptive Filter Pruning for Deep Model Compression
While convolutional neural networks (CNN) have achieved impressive perfo...
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03/11/2019
Accuracy Booster: Performance Boosting using Feature Map Re-calibration
Convolution Neural Networks (CNN) have been extremely successful in solv...
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03/11/2019
HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs
We present a novel deep learning architecture in which the convolution o...
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11/26/2018
Leveraging Filter Correlations for Deep Model Compression
We present a filter correlation based model compression approach for dee...
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11/20/2018
Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector
We propose a framework for compressing state-of-the-art Single Shot Mult...
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11/20/2018
Stability Based Filter Pruning for Accelerating Deep CNNs
Convolutional neural networks (CNN) have achieved impressive performance...
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03/28/2015
