{"m1":[],"m2":[],"m3":["resume_head","resume_name","resume_base_info","resume_job","resume_edu","resume_skill","resume_work","resume_internship","resume_honor","resume_project","resume_portfolio","resume_school_info","resume_hobby","resume_summary"],"m4":[]}
.resume_main[data_color] .skill_item .skill_slider span::before{background-color:${color};}
.resume_main[data_color] .skill_slider s i{background-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_01.skill_item .skill_slider s {border-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_01.skill_item .skill_slider s i{background-color:${relative_skill_color};}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="average"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="average"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 #ccc, 72px 0 0 #ccc, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="good"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="good"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 #ccc, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="advanced"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="advanced"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 ${relative_skill_color}, 96px 0 0 #ccc, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_04.skill_item .skill_slider[data_level="expert"] i,.resume_main[data_color] .skill_style_07.skill_item .skill_slider[data_level="expert"] i{box-shadow:24px 0 0 ${relative_skill_color}, 48px 0 0 ${relative_skill_color}, 72px 0 0 ${relative_skill_color}, 96px 0 0 ${relative_skill_color}, 120px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="average"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 #ccc,63px 0 0 #ccc,72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="good"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 #ccc,72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="advanced"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 ${relative_skill_color},72px 0 0 #ccc,81px 0 0 #ccc;}
.resume_main[data_color] .skill_style_08.skill_item .skill_slider[data_level="expert"] i{box-shadow:9px 0 0 ${relative_skill_color}, 18px 0 0 ${relative_skill_color}, 27px 0 0 ${relative_skill_color}, 36px 0 0 ${relative_skill_color}, 45px 0 0 ${relative_skill_color},54px 0 0 ${relative_skill_color},63px 0 0 ${relative_skill_color},72px 0 0 ${relative_skill_color},81px 0 0 #ccc;}
.resume_main[data_color] .hobby_item .hobby_item_con .hobby_item_list a.alifont{border-color:${relative_hobby_color};color:${relative_hobby_color}; }
/* ������ */
.resume_main[data_color] .resume_cover .cover_html svg [data-svg="fill"] {fill:${color};}
.resume_main[data_color] .resume_cover .cover_html svg [data-svg="stroke"] {stroke:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-svg="fill"] {fill:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-svg="stroke"] {stroke:${color};}
.resume_main[data_color] .resume_letter .letter_html svg [data-fill="fill"] {fill:${color};}
.resume_main[data_color] .resume_cover[data-type="07"] .resume_cover_avatar{border-color: ${color};}
.resume_main[data_color] .resume_cover[data-type="07"] .resume_cover_content{background:${color}}
.resume_main[data_color] .resume_cover[data-type="07"] .cover_item_list a.alifont{color: ${color};}
.resume_main[data_color] .resume_cover[data-type="08"] .resume_cover_content::after{background:${color}}
.resume_main[data_color] .resume_cover[data-type="09"] .resume_cover_content{background:${color}}
.resume_main[data_color] .resume_cover[data-type="09"] .cover_item_list a.alifont{color: ${color};}
.resume_main[data_color] .resume_cover[data-type="10"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="11"] .resume_cover_content{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="14"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="15"]{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="19"] .resume_cover_word::before{background-color:${color}}
.resume_main[data_color] .resume_cover[data-type="20"]{background-color:${color}}
.resume_main[data_color] .resume_letter[data-type="06"]{background-color:${color}}
.resume_main[data_color] .resume_letter[data-type="12"]{background-color:${color}}
.resume_main[data_color] .resume_m1:before,.resume_main[data_color] .resume_m1:after{color:${color};}
.resume_main[data_color] .resume_item dl dt span.resume_item_title_span{background-color:${color};}
.resume_main[data_color] .resume_m1{border-bottom-color:${color}52;}
["sex","age","nation","education","marriageStatus","politicalStatus","city","jobYear","mobile","email"]
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基本信息
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姓名
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锤子简历
梦想每个人都有,但不是每个人都有勇气去坚信,我有!
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教育背景
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2014.09 - 2018.06
锤子简历大学
计算机与信息技术
GPA:3.72/4(专业前10%) GRE:324
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工作经验
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2018年3月 - 至今
锤子简历信息有限公司
深度学习图像算法工程师
- 训练模型并编写脚本,实现从工作现场摄像头采集的视频中自动撷取大量适合检测的帧;
- 进行图像数据的预处理包括裁剪、增强、统一尺寸、归一化等,进行图像标注制成数据集;
- 构建的目标检测与分割模型并使用深度学习等方法利用获得的图像数据进行训练,对工业图像进行目标检测与实例分割,不仅实现自动侦测视频中含有目标的顿,还能够识别不同目标的类别和位置以及显示目标所覆盖的像素点;
- 在两种场景任务下分别实现不同目标的识别定位与长宽比统计和目标跟踪定位,满足工业场景需求,实现智能自动化检测;
- 根据应用场景的特点利用模型检测方法设计针对性的识别及跟踪定位策略,使用opencv将检测结果显示在视频流上,方便直观;
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项目经验
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2021年3月 - 2021年11月
项目工程
深度学习图像算法工程师
- 项目描述:在卷取机卷取钢材的过程中需要对钢材的尾部位置进行跟踪从而通过调节卷取机旋转速度将钢卷尾部停止在指定位置,便于下一步工序运行。钢带在卷取过程中需要判断尾部形状从而决定钢带的类型以及卷取的最佳位置,目前卷取机钢带尾部形状分类以及位置识别都是采用人工方式,费时费力且容易出错,项目方案采用基于机器视觉的图像识别、目标追踪等方法实现对带钢尾部形状的自动分类以及带钢尾部位置的实时跟踪,可实现尾部识别以及跟踪的自动化并给出控制信号控制卷取机停止位置,极大减少人力成本。
- 责任描述:开发代码实现从原始视频数据中自动筛选符合算法应用场景的顿;
- 获取图像数据后的相关处理(清洗、标注等),并制作数据集;
- 设计并训练深度学习模型实现卷取机带钢尾部的形状分类;
- 设计数据统计算法统计模型输出分类及位置结果并计算尾部长宽比;
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自我评价
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本人对待工作踏实,认真,并且极富工作和团队精神,因此在工作和生活中结交了许多朋友,具有良好的适应性和熟练的沟通技巧,相信能够协助主管人员出色地完成各项工作。综合素质佳,能够吃苦耐劳,忠诚稳重坚守诚信正直原则,感谢您在百忙之中阅览我的简历,静候佳音!
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作品展示
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+(支持jpg/png格式,单张图片不超过2M,最多支持添加8张图片)