Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
C-Rank Grade: D (Risky) - 8/100
External PR Merge Rate: -
Response Time: -
First Timer Success: -
sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow has a recorded first-timer success rate of 0.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 8.0 places sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow in the D tier.
The external contributor pull request merge rate for sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow is 0.0%, based on public PR activity from non-core contributors.
sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.
Active maintainer team in sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow welcoming community pull requests and bug fixes.
Discussions in sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.
Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.
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External Acceptance Rate
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First PR Conversion
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First PR success rate
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Maintainer review activity heatmap
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (81% approval). Large PRs (>500 lines) take ~115 hours (29% approval). Keep your diff compact for rapid review.
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When evaluating whether to contribute to sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.
sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow has a recorded first-timer success rate of 0.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 8.0 places sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow in the Risky tier.
The external pull request merge rate is 0.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for sushant097/Handwritten-Line-Text-Recognition-using-Deep-Learning-with-Tensorflow are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.