| Type of Material: | Thesis |
| Title: | Multiple Lane Departure Warning System for Multiple Road Scenarios |
| Researcher: | SUVARNA DATTATRAYA SHIRKE |
| Guide: | UDAYAKUMAR, R |
| Department: | Department of Engineering and Technology(Computer Science and Engineering) |
| Publisher: | Bharath University, Chennai |
| Place: | Chennai |
| Year: | 2020 |
| Language: | English |
| Subject: | Computer Science | Computer Science Theory and Methods | Engineering and Technology | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2020; D15CS505 |
| Fulltext: | Shodhganga |
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| 008 | __ | 240918t2020||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454666 |
| 040 | __ | |aBHAU_600073|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aSUVARNA DATTATRAYA SHIRKE|eResearcher |
| 110 | __ | |aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein |
| 245 | __ | |aMultiple Lane Departure Warning System for Multiple Road Scenarios |
| 260 | __ | |aChennai|bBharath University, Chennai|c2020 |
| 300 | __ | |dDVD |
| 502 | __ | |bPhD|cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai|d2020|oD15CS505 |
| 520 | __ | |aThe recent technologies in the advanced driver assistance systems lead to the development of various techniques for improving driver safety and automating the driving. One such development is the Lane Departure Warning (LDW) system, wherein lane detection techniques are employed for the detection of lanes to avoid road accidents. Accordingly, in the research work, three methods are proposed for lane detection. The first proposed method for multiple lane detection is implemented based on image transformation and proposed EW-CSA based Deep Convolution Neural Network (DCNN). Initially, the multiple lane images are transformed into Bird s eye view images. Next, the detection of the lane is carried out by proposed an Earth Worm- Crow Search Algorithm (EW-CSA) based DCNN. The Earth Worm-Crow Search Algorithm was proposed by merging EWA and CSA. This merged algorithm is used as the training algorithm in the DCNN. The second proposed method a region-based segmentation approach. It will detect the multiple. Here, th |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aComputer Science |
| 653 | __ | |aComputer Science Theory and Methods |
| 653 | __ | |aEngineering and Technology |
| 700 | __ | |aUDAYAKUMAR, R|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/310052|yShodhganga |
| 905 | __ | |afromsg |
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