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ahcd proposed dataset  (SoftMax Inc)

 
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    Structured Review

    SoftMax Inc ahcd proposed dataset
    A summary of related work on handwritten Arabic character recognition for adult writers.
    Ahcd Proposed Dataset, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/ahcd proposed dataset/product/SoftMax Inc
    Average 90 stars, based on 1 article reviews
    ahcd proposed dataset - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination"

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    Journal: Sensors (Basel, Switzerland)

    doi: 10.3390/s23156774

    A summary of related work on handwritten Arabic character recognition for adult writers.
    Figure Legend Snippet: A summary of related work on handwritten Arabic character recognition for adult writers.

    Techniques Used:

    A summary of related work on handwritten Arabic character recognition for child writers.
    Figure Legend Snippet: A summary of related work on handwritten Arabic character recognition for child writers.

    Techniques Used:

    Description of the used datasets.
    Figure Legend Snippet: Description of the used datasets.

    Techniques Used: Isolation

    Some preprocessed Hijja and AHCD character data samples: ( a ) Child writers’ samples; ( b ) Adult writers’ samples.
    Figure Legend Snippet: Some preprocessed Hijja and AHCD character data samples: ( a ) Child writers’ samples; ( b ) Adult writers’ samples.

    Techniques Used:

    An overview of conducted experimental work.
    Figure Legend Snippet: An overview of conducted experimental work.

    Techniques Used:

    Statistics of the used datasets.
    Figure Legend Snippet: Statistics of the used datasets.

    Techniques Used: Biomarker Discovery

    Child character recognition results of Experiment 1, using Hijja for training and testing.
    Figure Legend Snippet: Child character recognition results of Experiment 1, using Hijja for training and testing.

    Techniques Used:

    Child character recognition results of Experiment 2, using AHCD for training and Hijja for testing.
    Figure Legend Snippet: Child character recognition results of Experiment 2, using AHCD for training and Hijja for testing.

    Techniques Used:

    Child character recognition results of Experiment 3, using combined Hijja and AHCD for training and Hijja for testing.
    Figure Legend Snippet: Child character recognition results of Experiment 3, using combined Hijja and AHCD for training and Hijja for testing.

    Techniques Used:

    Writer-group classification performance of Experiment 4, without supplementary features using combined Hijja and AHCD for training and testing.
    Figure Legend Snippet: Writer-group classification performance of Experiment 4, without supplementary features using combined Hijja and AHCD for training and testing.

    Techniques Used:

    Writer-group classification performance of Experiment 5, with supplementary features using combined Hijja and AHCD for training and testing.
    Figure Legend Snippet: Writer-group classification performance of Experiment 5, with supplementary features using combined Hijja and AHCD for training and testing.

    Techniques Used:

    Comparison between our proposed methodology and current approaches in the literature.
    Figure Legend Snippet: Comparison between our proposed methodology and current approaches in the literature.

    Techniques Used: Comparison, Extraction



    Similar Products

    ahcd proposed dataset  (SoftMax Inc)
    90
    SoftMax Inc ahcd proposed dataset
    A summary of related work on handwritten Arabic character recognition for adult writers.
    Ahcd Proposed Dataset, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/ahcd proposed dataset/product/SoftMax Inc
    Average 90 stars, based on 1 article reviews
    ahcd proposed dataset - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    A summary of related work on handwritten Arabic character recognition for adult writers.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: A summary of related work on handwritten Arabic character recognition for adult writers.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    A summary of related work on handwritten Arabic character recognition for child writers.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: A summary of related work on handwritten Arabic character recognition for child writers.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Description of the used datasets.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Description of the used datasets.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques: Isolation

    Some preprocessed Hijja and AHCD character data samples: ( a ) Child writers’ samples; ( b ) Adult writers’ samples.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Some preprocessed Hijja and AHCD character data samples: ( a ) Child writers’ samples; ( b ) Adult writers’ samples.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    An overview of conducted experimental work.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: An overview of conducted experimental work.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Statistics of the used datasets.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Statistics of the used datasets.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques: Biomarker Discovery

    Child character recognition results of Experiment 1, using Hijja for training and testing.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Child character recognition results of Experiment 1, using Hijja for training and testing.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Child character recognition results of Experiment 2, using AHCD for training and Hijja for testing.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Child character recognition results of Experiment 2, using AHCD for training and Hijja for testing.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Child character recognition results of Experiment 3, using combined Hijja and AHCD for training and Hijja for testing.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Child character recognition results of Experiment 3, using combined Hijja and AHCD for training and Hijja for testing.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Writer-group classification performance of Experiment 4, without supplementary features using combined Hijja and AHCD for training and testing.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Writer-group classification performance of Experiment 4, without supplementary features using combined Hijja and AHCD for training and testing.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Writer-group classification performance of Experiment 5, with supplementary features using combined Hijja and AHCD for training and testing.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Writer-group classification performance of Experiment 5, with supplementary features using combined Hijja and AHCD for training and testing.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques:

    Comparison between our proposed methodology and current approaches in the literature.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Deep Learning-Based Child Handwritten Arabic Character Recognition and Handwriting Discrimination

    doi: 10.3390/s23156774

    Figure Lengend Snippet: Comparison between our proposed methodology and current approaches in the literature.

    Article Snippet: [ ] , 2021 , CNN , Softmax , AHCD Proposed dataset Hijja MNIST , Characters Characters Characters Digits , 16,800 38,100 47,434 70,000 , 99% 95.4% 90% 99%.

    Techniques: Comparison, Extraction