Handwritten Digit Recognition based on DWT and DCT

Lawgali, Ahmed

doi:10.14257/ijdta.2015.8.5.18

Cited by 12 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In (Lawgali, 2015), the author proposes a method for capturing the properties of handwritten digit that is based on DWT and DCT. ANN is used during the classification step.…”

Section: Evaluating the Effectiveness Of The Proposed D-snnmentioning

confidence: 99%

Histopathology of Post Immunization and Chemotherapeutic Trials in Experimental Cystic Echinococcosis

SADEK¹,

ALI²

2022

Full Text Book of Minar Congress 6

View full text Add to dashboard Cite

The present study in mice concerned about the immunized mice by Hydatid cystic fluid (HCFAgs) and treated with three anthelmintic drugs alone Albendazole (ABZ), Oxfendazole (OFZ) and Praziquental (PZQ) or in combined ABZ+ PZQ, OFZ + ABZ and OFZ+PZQ. Treatment with OFZ shows 93.75% efficacy, but it's more effective in combination with PZQ (96.7%), but it lower in combination with ABZ 82.5% or ABZ combined with PZQ 77.5%.The sera of the mice were screened for the biochemical enzymes. Liver and spleen were processed and paraffin embedded tissue sections were examined by immunohistochemistry (IHC) for IFN-gamma from different study groups. After treatment, liver and spleen express an increased IFN-ɣ protein in treated groups and positive control group compared with control negative group. We have evaluated of the pathological changes in liver and spleen of mice after four months of the infection and treatment. The result showed satisfactory histopathological changes in comparison with positive control group.

show abstract

“…In (Lawgali, 2015), the author proposes a method for capturing the properties of handwritten digit that is based on DWT and DCT. ANN is used during the classification step.…”

Section: Evaluating the Effectiveness Of The Proposed D-snnmentioning

confidence: 99%

Histopathology of Post Immunization and Chemotherapeutic Trials in Experimental Cystic Echinococcosis

SADEK¹,

ALI²

2022

Full Text Book of Minar Congress 6

View full text Add to dashboard Cite

show abstract

“…This recognition capability is very useful and can be utilized in many applications in a variety of systems and purposes. Therefore, this research field has recently received some research interests [16], [18]- [20]. For the sake of creating databases of Arabic-Indic digit samples and providing them for further research work, a number of research works have produced such databases and introduced them with initial studies/results to be used as benchmarks for future studies [15], [21], [22].…”

Section: Introductionmentioning

confidence: 99%

“…A number of well-known techniques, which were introduced for other machine learning and pattern recognition applications, may also be used in a diversity of character and digit recognition contexts [1], [2], [24]. Artificial Neural Network (ANN) as an example, has been excessively applied in different topologies for learning to recognize and classify characters and numerals [23], such as Multilayer [7], [18], [21], Probabilistic [3], Convolutional [6], [19], [25], and Back Propagation [9], [10], [14], [20] Neural Networks. Moreover, other common classification methods were employed and found useful for attaining high recognition rates such as single- [13], [22] or multi-Nearest Neighbor [18], Support Vector Machine (SVM) [11], [13], [22], Deep Learning [23], [25], and Random Oblique Decision Trees [12].…”

Section: Introductionmentioning

confidence: 99%

Efficient Gabor-Based Recognition for Handwritten Arabic-Indic Digits

Jaha¹

2019

ijacsa

View full text Add to dashboard Cite

In daily life, the need of automatically digitizing paper documentations and recognizing textual images is still present with existing and potential upcoming rooms for improvements, especially for languages like Arabic, which is unlike English as an instance, has more complex context and not been extensively supported by research in a such domain. As yet, the available online offline optical character recognition (OCR) systems have utilized functional techniques and achieved high performance mainly on machine printed data images. However, in case of handwritten script, the recognition task becomes highly unconstrained and much more challenging. Amongst a large verity of recognizable multilingual characters, handwritten digit recognition is a considerably useful task for different purposes and countless applications. In this research, the focus is on Arabic (known today as Indic or Indian) digit recognition using different proposed Gabor-based approaches in several combinations with different classification methods. The proposed approaches are trained and tested using 91120 digit samples of two independent standard databases (Arabic-Handwritten-Digits and AHDBase), allowing performance variability assessments and comparisons not only between the different combinations of features and classifiers but also between different datasets. The proposed Arabic-Indic digit recognition system achieves high recognition rates reach up to 99.87%. This research practically shows that one of the proposed approaches with significant dimensionality reduced features remains attaining a high recognition rate with low complexity time, which can be hence recommended further for online digit recognition systems.

show abstract