Dipanjyoti Paul

Prompt-CAM

Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu et autres

Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis

Arpita Roy Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu et autres

We present a simple approach to make pre-trained Vision Transformers (ViTs) interpretable for fine-grained analysis, aiming to identify and localize the traits that distinguish visually similar categories, such as bird species. Pretrained ViTs, such as DINO, have demonstrated remarkable capabilities in extracting …

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Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis

Arpita Roy Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu et autres

We present a simple approach to make pre-trained Vision Transformers (ViTs) interpretable for fine-grained analysis, aiming to identify and localize the traits that distinguish visually similar categories, such as bird species. Pre-trained ViTs, such as DINO, have demonstrated remarkable capabilities in extracting …

Online Summarization of Microblog Data: An Aid in Handling Disaster Situations

Dipanjyoti Paul, Shivani Rana, Sriparna Saha, Jimson Mathew

During any natural disaster or unfortunate accident, both civilians and responders need information on an urgent basis. In such events, microblogging sites particularly Twitter plays an important role in providing real-time information. The raw form of microblog tweets is prodigiously informative but …

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A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

Dipanjyoti Paul, Arpita Roy Chowdhury, Xinqi Xiong, Feng-Ju Chang et autres

We present a novel usage of Transformers to make image classification interpretable. Unlike mainstream classifiers that wait until the last fully connected layer to incorporate class information to make predictions, we investigate a proactive approach, asking each class to search for itself …

Online Research Topic Modeling and Recommendation Utilizing Multiview Autoencoder-Based Approach

Dipanjyoti Paul, Daipayan Chakdar, Sriparna Saha, Jimson Mathew

Recent years have witnessed tremendous growth in the publication of research articles as well as in the rise of new research topics. Articles get published in a streaming manner and therefore retrieving and recommending trending topics continuously by updating the trend of …

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ML-KnockoffGAN: Deep online feature selection for multi-label learning

Dipanjyoti Paul, Snigdha Bardhan, Sriparna Saha, Jimson Mathew

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Multiview Deep Online Clustering: An Application to Online Research Topic Modeling and Recommendations

Dipanjyoti Paul, Daipayan Chakdar, Sriparna Saha, Jimson Mathew

In today’s scenario, a large number of scientific articles on various domains are being published everyday, resulting in a rapid change in the trends of research topics. Retrieving the trending topics, evaluating the trends and extracting the scope of topics could be …

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Multi-layer perceptron for detection of different class antibiotics from visual fluorescence response of a carbon nanoparticle-based multichannel array sensor

Saptarshi Mandal, Dipanjyoti Paul, Sriparna Saha, Prolay Das

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Generative Adversarial Nets Boosted Multi-Layer Perceptron for Detection of Toxic Heavy Metal Ions Based on Visual Fluorescence Response from Carbon Nanoparticles Array

Saptarshi Mandal, Dipanjyoti Paul, Sriparna Saha, Prolay Das

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Multi-Layer Perceptron for Detection of Different Class Antibiotics from Visual Fluorescence Response of a Carbon Nanoparticle-Based Multichannel Array Sensor

Saptarshi Mandal, Dipanjyoti Paul, Sriparna Saha, Prolay Das

in (code pays fourni par la source)

Deep learning assisted detection of toxic heavy metal ions based on visual fluorescence responses from a carbon nanoparticle array

Saptarshi Mandal, Dipanjyoti Paul, Sriparna Saha, Prolay Das

A carbon nanoparticle-based visual fluorescent array sensing–artificial intelligence (deep learning) integrated platform for remote detection of toxic heavy metal ions.

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