S M Rayeed

BeetleFlow: An Integrative Deep Learning Pipeline for Beetle Image Processing

Fangxun Liu, S M Rayeed, Samuel Stevens, Alyson East et autres

In entomology and ecology research, biologists often need to collect a large number of insects, among which beetles are the most common species. A common practice for biologists to organize beetles is to place them on trays and take a picture of …

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Optimizing image capture for computer vision‐powered taxonomic identification and trait recognition of biodiversity specimens

Alyson East, Elizabeth Campolongo, Luke Meyers, S M Rayeed et autres

Abstract Biological collections house millions of specimens with digital images increasingly available through open‐access platforms. However, most imaging protocols were developed for human interpretation without considering automated analysis requirements. As computer vision applications revolutionize taxonomic identification and trait extraction, a critical gap …

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Fine-Grained Taxonomy with Vision Models: A Benchmark on Long-Tailed and Domain-Adaptive Classification

S M Rayeed, Alyson East, Samuel Stevens, Sydne Record et autres

Ground beetles are a highly sensitive and speciose biological indicator, critical for biodiversity monitoring, yet their taxonomic classification remains underutilized due to the manual effort required for species differentiation based on subtle morphological variations. In this paper, we present a benchmark for …

Mind the (Data) Gap: Evaluating Vision Systems in Small Data Applications

Samuel Stevens, S M Rayeed, Jenna Kline

The practical application of AI tools for specific computer vision tasks relies on the "small-data regime" of hundreds to thousands of labeled samples. This small-data regime is vital for applications requiring expensive expert annotations, such as ecological monitoring, medical diagnostics or industrial …

BdSL47: A complete depth-based Bangla sign alphabet and digit dataset

S M Rayeed, Sidratul Tamzida Tuba, Hasan Mahmud, Md. Mumtahin Habib Ullah Mazumder et autres

Sign Language Recognition (SLR) is crucial for enabling communication between the deaf-mute and hearing communities. Nevertheless, the development of a comprehensive sign language dataset is a challenging task due to the complexity and variations in hand gestures. This challenge is particularly evident …

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BdSL47: A complete dataset of sign alphabet and digits of Bangla Sign Language (BdSL) using depth information via MediaPipe

S M Rayeed

The dataset contains 47000 RGB input images of 47 signs (10 digits, 37 letters) of Bangla Sign Language. The images have been processed via MediaPipe framework, which is designed to detect predefined 21 hand key-points from a sample and provide normalized x …

Bangla sign digits recognition using depth information

S M Rayeed, Gazi Wasif Akram, Sidratul Tamzida Tuba, Golam Sadman Zilani et autres

Sign Language Recognition (SLR) targets on interpreting the sign language into text or speech, so as to facilitate the communication between deaf-mute people and ordinary people. The task has broad social impact, but is still very challenging due to the complexity and …

bd (code pays fourni par la source)

Bdsl47: A Complete Open-Access Depth-Based Bangla Sign Alphabet and Digit Dataset

S M Rayeed, Sidratul Tamzida Tuba, Hasan Mahmud, Md. Saddam Hossain Mukta et autres

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