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Found 18 papers, 7 papers with code
Multi-Scale Fusion Methodologies for Head and Neck Tumor Segmentation
Head and Neck (H\&N) organ-at-risk (OAR) and tumor segmentations are essential components of radiation therapy planning.
An Efficient Multi-Scale Fusion Network for 3D Organ at Risk (OAR) Segmentation
Accurate segmentation of organs-at-risks (OARs) is a precursor for optimizing radiation therapy planning.
Video Capsule Endoscopy Classification using Focal Modulation Guided Convolutional Neural Network
We compare our FocalConvNet with other SOTA on Kvasir-Capsule, a large-scale VCE dataset with 44, 228 frames with 13 classes of different anomalies.
Automatic Polyp Segmentation with Multiple Kernel Dilated Convolution Network
The detection and removal of precancerous polyps through colonoscopy is the primary technique for the prevention of colorectal cancer worldwide.
PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation
We develop progressive alternating attention dense (PAAD) blocks, which construct a guiding attention map (GAM) after every convolutional layer in the dense blocks using features from all scales.
GMSRF-Net: An improved generalizability with global multi-scale residual fusion network for polyp segmentation
The repeated fusion operations gated by CMSA and MSFS demonstrate improved generalizability of the network.
Ranked #13 on
Medical Image Segmentation
on Kvasir-SEG
Exploiting Multi-Scale Fusion, Spatial Attention and Patch Interaction Techniques for Text-Independent Writer Identification
Our methods are based on the hypothesis that handwritten text images have specific spatial regions which are more unique to a writer's style, multi-scale features propagate characteristic features with respect to individual writers and patch-based features give more general and robust representations that helps to discriminate handwriting from different writers.
AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for Face Hallucination
The performance of facial super-resolution methods relies on their ability to recover facial structures and salient features effectively.
An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data
In this work, we extend our previous work by proposed an efficient iForest based approach for anomaly detection using cube sampling that is effective on streaming data.
An Energy Efficient Health Monitoring Approach with Wireless Body Area Networks
In addition to being able to handle streaming data, the model works within the resource-constrained environments of an LPU and eliminates the need of transmitting the data to a back-end cloud, ensuring further energy savings.
A mmWave Oscillator Design Utilizing High-Q Active-Mode On-Chip MEMS Resonators for Improved Fundamental Limits of Phase Noise
(RFT) allows very high-Q active mode resonators, promising crystal-less monolithic clock generation for mmWave systems.
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
The proposed MSRF-Net allows to capture object variabilities and provides improved results on different biomedical datasets.
Ranked #3 on
Medical Image Segmentation
on 2018 Data Science Bowl
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
To address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval.
Ranked #1 on
Argument Retrieval
on ArguAna (BEIR)
Conditional Hybrid GAN for Sequence Generation
Conditional sequence generation aims to instruct the generation procedure by conditioning the model with additional context information, which is a self-supervised learning issue (a form of unsupervised learning with supervision information from data itself).
Building a User-Generated Content North-African Arabizi Treebank: Tackling Hell
We introduce the first treebank for a romanized user-generated content variety of Algerian, a North-African Arabic dialect known for its frequent usage of code-switching.
Analysis and Design Considerations for Achieving the Fundamental Limits of Phase Noise in mmWave Oscillators with On-Chip MEMS Resonator
Very small electromechanical coupling coefficient in micro-electromechanical systems (MEMS) or acoustic resonators is quite of a concern for oscillator performance, specially at mmWave frequencies.
Understanding Script-Mixing: A Case Study of Hindi-English Bilingual Twitter Users
Our analysis shows that both intra-sentential and inter-sentential script-mixing are present on Twitter and show different behavior in different contexts.
Conditional LSTM-GAN for Melody Generation from Lyrics
Melody generation from lyrics has been a challenging research issue in the field of artificial intelligence and music, which enables to learn and discover latent relationship between interesting lyrics and accompanying melody.
