Cell-TRACTR detects cells in the first frame at time t 0. Object queries predicted to be a “cell” are converted to track queries. For Track Group Denoising (TGD), random noise is a... by Owen M. O’Connor (11965460)

Cells are initially detected in frame t₀ and then tracked to frame t₁. Object queries are processed in the first layer of the decoder for object detection. In... by Owen M. O’Connor (11965460)

Effect of segmentation mask resolution on CUDA memory usage and performance metrics. (A) Memory usage as a function of queries when Cell-TRACTR produces a segmentation mask with th... by Owen M. O’Connor (11965460)

Visual representation of how Cell-TRACTR uses track queries to track cells and detect divisions. by Owen M. O’Connor (11965460)

Example illustrating how object and track queries interact using an attention map processed by Cell-TRACTR across two subsequent frames. The schematic displays the actual output al... by Owen M. O’Connor (11965460)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

Subjects: “…Cell Biology…”

Comparison of inference speed and model size for different tracking algorithms. by Yinghong Xie (22319875)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

The encoder employs deformable self-attention to transform multi-scale features into encoded multi-scale features. Query selection is used to derive the object queries from these e... by Owen M. O’Connor (11965460)

(A) Example illustrating the correlation between the final prediction of an object query and where the object query is derived from within the multi-scale features. Colored pixels... by Owen M. O’Connor (11965460)

Overview of the Cell2Spatial algorithm. by Huamei Li (8815955)

Subjects: “…Cell Biology…”

Elements: Kingfisher: Storage Management for Data Federations (CSSI PI Meeting 2025) by Brian Bockelman (5128082)

Heatmap illustrating which multi-scale feature pixels were classified as “cell” by query selection. This data was collected by processing the full test set for the DeepCell dataset... by Owen M. O’Connor (11965460)

Algorithm testing. by Ziad M. Ali (12516532)

Subjects:

Risk element category diagram. by Yao Hu (3479972)

Supplementary file 1_Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules.docx by Fatima Wardi (22052360)

“…The extracted parameters for each case study are used to reconstruct the I–V and power–voltage (P–V) characteristic curves for the respective solar cell and photovoltaic module technologies. To validate the performance and efficiency of the algorithm, various statistical criteria are computed, including individual absolute error (IAE), relative error (RE), root mean square error (RMSE), mean absolute error (MAE), standard deviation (SD), tracking signal (TS), normalized forecast measure (NFM), and the autocorrelation function (ACF). …”

Convergence curves of the investigated algorithms. by Ziad M. Ali (12516532)

Subjects:

Visual representation of Trust and elements that are needed for equitable data sharing. by Qunita Brown (19751520)

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Heatmap illustrating which multi-scale feature pixels were classified as “cell” by query selection. This data was collected by processing the full test set containing 29 movies fro... by Owen M. O’Connor (11965460)