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Object recognition is among the fundamental tasks in the computer vision applications, paving the path for all other image understanding operations. In every stage of progress in object recognition research, efforts have been made to…
We report on optical searches in the error circles of 93 ROSAT survey sources located at low galactic latitudes (|b| < 20 deg). These sources were extracted from the ROSAT Galactic Plane Survey using various selection criteria on hardness…
Gravitational microlensing of gamma-ray bursts (GRBs) provides a unique opportunity to probe compact dark matter and small-scale structures in the Universe. However, identifying such microlensed GRBs within large data sets is a significant…
We present 22\,901 OB spectra of 16\,032 stars identified from LAMOST DR5 dataset. A larger sample of OB candidates are firstly selected from the distributions in the spectral line indices space. Then all 22\,901 OB spectra are identified…
In Kigali, Rwanda, motorcycle taxis are a primary mode of transportation, often navigating unpredictably and disregarding traffic rules, posing significant challenges for autonomous driving systems. This study compares four object detection…
Particle track reconstruction is the most computationally intensive process in nuclear physics experiments. Traditional algorithms use a combinatorial approach that exhaustively tests track measurements ("hits") to identify those that form…
The development of multi-label deep learning models for retinal disease classification is often hindered by the scarcity of large, expertly annotated clinical datasets due to patient privacy concerns and high costs. The recent release of…
Chest X-ray imaging remains the primary diagnostic tool for pulmonary and cardiac disorders worldwide, yet its accuracy is hampered by radiologist shortages and inter-observer variability. This study presents a systematic comparative…
The LHCb (Large Hadron Collider beauty) experiment at CERN aims at achieving a significantly higher luminosity than originally planned by means of two major upgrades: the Upgrade I that took place during the Long Shutdown 2 (LS2) and the…
We present the HI data for 5 spiral galaxies that, along with their Halpha rotation curves, are used to derive the distribution of dark matter within these objects. A new method for extracting rotation curves from HI data cubes is…
Underwater pollution is one of today's most significant environmental concerns, with vast volumes of garbage found in seas, rivers, and landscapes around the world. Accurate detection of these waste materials is crucial for successful waste…
Twenty-three machine learning algorithms were trained then scored to establish baseline comparison metrics and to select an image classification algorithm worthy of embedding into mission-critical satellite imaging systems. The…
This study evaluates the effectiveness of deep learning models in classifying histopathological images for early and accurate detection of breast cancer. Eight advanced models, including ResNet-50, DenseNet-121, ResNeXt-50, Vision…
Autonomous vision-based spaceborne navigation is an enabling technology for future on-orbit servicing and space logistics missions. While computer vision in general has benefited from Machine Learning (ML), training and validating…
The Fermi fourth catalog of active galactic nuclei (AGNs) data release 3 (4LAC-DR3) contains 3407 AGNs, out of which 755 are flat spectrum radio quasars (FSRQs), 1379 are BL Lacertae objects (BL Lacs), 1208 are blazars of unknown (BCUs)…
Detached eclipsing binary stars (dEBs) are a key source of data on fundamental stellar parameters. Within the light curve databases of survey missions such as Kepler and TESS are a wealth of new systems awaiting characterisation. We aim to…
Aims. The CoRoT space mission continues to photometrically monitor about 12 000 stars in its field-of-view for a series of target fields to search for transiting extrasolar planets ever since 2007. Deep transit signals can be detected…
There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy. Practical testing of combinations of such features on large datasets, and theoretical justification of the result, is required. Some…
Clusters of galaxies in most previous catalogs have redshifts z<0.3. Using the photometric redshifts of galaxies from the Sloan Digital Sky Survey Data Release 6 (SDSS DR6), we identify 39,668 clusters in the redshift range 0.05< z <0.6…
The efficient classification of different types of supernova is one of the most important problems for observational cosmology. However, spectroscopic confirmation of most objects in upcoming photometric surveys, such as the The Rubin…