All categories
Development
Programming, frameworks, implementation, frontend, backend, and app development
- 70,058
- 2,920
Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.
Open in full browserBrowse development skills
Showing 19,729–19,752 of 70,058 skills
- Frame Differencing Temporal EncodingEncode motion and velocity by computing per-channel pixel differences between consecutive frames instead of stacking raw frames for RL visual observationsVotes: 0GitHub stars: 61
- Focal LossAlpha-weighted focal loss that down-weights easy examples to focus training on hard, misclassified pixels in imbalanced segmentation tasks.Votes: 0GitHub stars: 61
- Flat Multicondition HeadModels multiple conditions with a single flat output layer of N_labels × N_classes logits, sliced into per-condition softmax at inference.Votes: 0GitHub stars: 61
- Exam Sequence Padded Mask LossPad variable-length per-slice sequences to a fixed batch length, carry a 0/1 mask alongside, and multiply per-slice BCE by the mask before reducing — gives correct per-exam loss with batched training and zero contamination from padding tokensVotes: 0GitHub stars: 61
- Dual View Reshape ForwardReshape dual-view stacked channels into doubled batch dimension for shared backbone, then concatenate with tabular features for classificationVotes: 0GitHub stars: 61
- Differentiable Soft F1 LossUse a soft macro-F1 loss `1 − mean(2·tp / (2·tp + fp + fn))` computed from raw sigmoid probabilities (no thresholding) as a direct training objective for multi-label classification, optionally combined with BCE — closes the gap between training surrogate and the F1 metric the leaderboard scoresVotes: 0GitHub stars: 61
- Dicom Voi Lut PreprocessingRead DICOM X-ray files with VOI LUT transformation and MONOCHROME1 inversion for correct pixel intensity renderingVotes: 0GitHub stars: 61
- Dicom Orientation DetectionDecodes MRI scan plane (axial, coronal, sagittal) from DICOM ImageOrientationPatient direction cosine vectors.Votes: 0GitHub stars: 61
- Dice LossDice coefficient loss for pixel-level segmentation that directly optimizes the overlap between predicted and ground-truth masks.Votes: 0GitHub stars: 61
- Conv1d Lstm Stroke ClassifierStack 1D convolutions for local feature extraction before bidirectional LSTMs to classify variable-length stroke sequences into hundreds of doodle categoriesVotes: 0GitHub stars: 61
- Connected Components Centroid ExtractionExtracts object centers from 3D segmentation masks using connected-component labeling and centroid computation.Votes: 0GitHub stars: 61
- Concat Tile Feature PoolingPasses N tiles independently through a shared CNN backbone, concatenates their feature maps spatially, then pools for classification — a lightweight multi-instance learning approach.Votes: 0GitHub stars: 61
- Cnn Metadata Fusion HeadFuse CNN image features with a small tabular MLP branch via concat before a final classifier, training both branches end-to-endVotes: 0GitHub stars: 61
- Cnn Encoder Spatial Feature MapStrips the global pool and FC head from a pretrained CNN to expose spatial feature maps (H x W x C) for attention-based decoding.Votes: 0GitHub stars: 61
- Center Z Slice SelectionSelect a fixed number of Z-slices centered around the volume midpoint for memory-efficient 2.5D input from 3D CT/MRI stacksVotes: 0GitHub stars: 61
- Black Slice ReplacementDetect all-black DICOM/MRI slices (mean==0) and replace them by randomly sampling a non-black slice from the same seriesVotes: 0GitHub stars: 61
- Bigru Slice Feature AggregatorTwo-stage CT classifier where a 2D CNN dumps per-slice features once, then a bidirectional GRU runs over the slice sequence to produce both per-slice predictions (TimeDistributed head) and an exam-level prediction (avg+max pooled head) — turns expensive 3D CNN training into cheap sequence modelingVotes: 0GitHub stars: 61
- Bev Conv1 Channel ExpansionReplace a pretrained ResNet's conv1 with a wider input conv to accept stacked BEV raster channels (semantic map + agent history) while keeping downstream weightsVotes: 0GitHub stars: 61
- Anisotropic Spacing Trilinear ResampleResample a 3D medical volume to a fixed network input shape using physical voxel spacing (dz, dy, dx), correcting the Z dimension by the dz/dy ratio so anisotropic CT scans (1mm in-plane, 5mm slice) end up anatomically isotropic before trilinear interpolationVotes: 0GitHub stars: 61
- 3d Encoder 2d Decoder Segmentation3D ResNet encoder extracts volumetric features, pools depth dimension, then feeds into a 2D UNet/FPN decoder for segmentationVotes: 0GitHub stars: 61
- 2d To 3d Model ConversionConverts a pretrained 2D CNN into a 3D CNN by recursively replacing Conv2d/BN2d/Pool2d layers and inflating kernel weights along the depth axis.Votes: 0GitHub stars: 61
- nuxt-swiftsearchImplement Algolia search UIs in Nuxt 3 apps using @atoms-studio/nuxt-swiftsearch — an SSR-first, fully typed alternative to vue-instantsearch.Votes: 0GitHub stars: 66
- Review DocsReview documentation for quality, clarity, SEO, and technical correctness. Optimized for Docus/Nuxt Content but works with any Markdown documentation. Use when asked to: "review docs", "check documentation", "audit docs", "validate documentation", "improve docs quality", "analyze documentation", "check my docs", "review my documentation pages", "validate MDC syntax", "check for SEO issues", "analyze doc structure". Provides actionable recommendations categorized by priority (Critical, Importa...Votes: 0GitHub stars: 66
- Explain IssueExplain a cargo-coupling issue type or reported finding, including detection limits and possible remedies.Votes: 0GitHub stars: 109