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Found 22 papers, 5 papers with code
Efficient Movie Scene Detection using State-Space Transformers
Given a sequence of frames divided into movie shots (uninterrupted periods where the camera position does not change), the S4A block first applies self-attention to capture short-range intra-shot dependencies.
A Novel Framework for Characterization of Tumor-Immune Spatial Relationships in Tumor Microenvironment
Understanding the impact of tumor biology on the composition of nearby cells often requires characterizing the impact of biologically distinct tumor regions.
A Systematic Review on Interactive Virtual Reality Laboratory
Virtual Reality has become a significant element of education throughout the years.
BLPnet: A new DNN model and Bengali OCR engine for Automatic License Plate Recognition
This paper reports a computationally efficient and reasonably accurate Automatic License Plate Recognition (ALPR) system for Bengali characters with a new end-to-end DNN model that we call Bengali License Plate Network(BLPnet).
Modelling Lips-State Detection Using CNN for Non-Verbal Communications
In contrast, the model with MediaPipe offers faster landmark detection capability with an average FPS of 20 and detection accuracy of 94. 4%.
The Case for High-Accuracy Classification: Think Small, Think Many!
Given the insight gained from our experiments, we hence propose a "think small, think many" philosophy in classification scenarios: that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, lightweight models with narrowed-down color spaces can possibly lead to predictions with higher accuracy.
Improving Multimodal Accuracy Through Modality Pre-training and Attention
Training a multimodal network is challenging and it requires complex architectures to achieve reasonable performance.
A Study of fastText Word Embedding Effects in Document Classification in Bangla Language
Such types of task in the Bangla language is also important.
Virtual Screening of Plant Metabolites against Main protease, RNA-dependent RNA polymerase and Spike protein of SARS-CoV-2: Therapeutics option of COVID-19
The molecular interaction study revealed that Rifampin (-16. 3 kcal/mol) were topmost inhibitor of MPP where Azobechalcone were found most potent plant therapeutics for blocking the RdRp (-15. 9 kcal /mol) and S (-14. 4 kcal/mol) protein of SARS-CoV-2.
Prediction of potential inhibitors for RNA-dependent RNA polymerase of SARS-CoV-2 using comprehensive drug repurposing and molecular docking approach
The pandemic prevalence of COVID-19 has become a very serious global health issue.
Biomolecules
Comparisonal study of Deep Learning approaches on Retinal OCT Image
In this research, we have taken such an attempt to detect retinal diseases from optical coherence tomography (OCT) X-ray images.
Prediction and Description of Near-Future Activities in Video
Most of the existing works on human activity analysis focus on recognition or early recognition of the activity labels from complete or partial observations.
Attack and Anomaly Detection in IoT Sensors in IoT Sites Using Machine Learning Approaches
The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN).
Context-Aware Query Selection for Active Learning in Event Recognition
We formulate a conditional random field model that encodes the context and devise an information-theoretic approach that utilizes entropy and mutual information of the nodes to compute the set of most informative queries, which are labeled by a human.
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net respectively.
Handwritten Bangla Character Recognition Using The State-of-Art Deep Convolutional Neural Networks
In spite of advances in object recognition technology, Handwritten Bangla Character Recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings.
Improved Inception-Residual Convolutional Neural Network for Object Recognition
In this paper, we introduce a new DCNN model called the Inception Recurrent Residual Convolutional Neural Network (IRRCNN), which utilizes the power of the Recurrent Convolutional Neural Network (RCNN), the Inception network, and the Residual network.
Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos
We propose a network similar to a hybrid Siamese network with three branches to jointly learn both the future label and the starting time.
Inception Recurrent Convolutional Neural Network for Object Recognition
Furthermore, we have investigated IRCNN performance against equivalent Inception Networks and Inception-Residual Networks using the CIFAR-100 dataset.
Learning Temporal Regularity in Video Sequences
Perceiving meaningful activities in a long video sequence is a challenging problem due to ambiguous definition of 'meaningfulness' as well as clutters in the scene.
Ranked #2 on
Traffic Accident Detection
on A3D
Context Aware Active Learning of Activity Recognition Models
We formulate a conditional random field (CRF) model that encodes the context and devise an information theoretic approach that utilizes entropy and mutual information of the nodes to compute the set of most informative query instances, which need to be labeled by a human.
Incremental Activity Modeling and Recognition in Streaming Videos
Most of the state-of-the-art approaches to human activity recognition in video need an intensive training stage and assume that all of the training examples are labeled and available beforehand.
